Abbar, Ali (2011), Predicting stock returns using linear and non-linear regression (case study: petrochemical industry), master's thesis, University of Sistan and Baluchistan 2) Abdullah, S. (2020). US Economic policy uncertainty and GCC stock market performance. Studies in Business and Economics, 15(1), 223-242.
3) Adham, Abbas; Marfoo, Mohammad; Ebrahimi Sarvolia, Mohammad Hassan (2021) Comparison of the explanatory power of linear and non-linear
models in order to predict the expected returns of stocks, Stock Exchange Quarterly, 14th year, number 56, winter 1400, pp. 140.-111 4) Amiri, Hossein; Pirdadeh Biranvand, Mehbobeh.(2018). Uncertainty of Iran's economic policies and stock market based on the Markov regime change approach. Financial knowledge of securities analysis, volume 12, number 44, pp: 67-49. 5) Amisano, G., & Geweke, J. (2017). Prediction using several macroeconomic models. Review of Economics and Statistics, 99(5), 912-925. 6) Anatolyev, S., & Gospodinov, N. (2007). Modeling financial return dynamics by decomposition (No. w0095). 7) Bagirov, M., & Mateus, C. (2019). Oil prices, stock markets and firm performance: Evidence from Europe. International Review of Economics & Finance, 61, 270-288. 8) Breen, W., Glosten, R., & Jagannathan, R. (1989). Economic significance of predictable variations in stock index returns. The Journal of finance, 44(5), 1177-1189. 9) Brooks, C. (2008). RATS Handbook to accompany introductory econometrics for finance. Cambridge Books. 10) Cales, L., Jondeau, E., &Rockinger, M. (2013).Long-Term portfolio management with a structural macroeconomic model. Swiss Finance Institute Research Paper, (13-45). 11) Campbell, J. Y., & Thompson, S. B. (2008). Predicting excess stock returns out of sample: Can anything beat the historical average?. The Review of Financial Studies, 21(4), 1509-1531. 12) Cenesizoglu, T., & Timmermann, A. (2012). Do return prediction models add economic value?. Journal of Banking & Finance, 36(11), 2974-2987. 13) Chatfield, C. (1993). Calculating interval forecasts. Journal of Business & Economic Statistics, 11(2), 121-135. 14) Christoffersen, P. F., & Diebold, F. X. (2006). Financial asset returns, direction-of-change forecasting, and volatility dynamics. Management Science, 52(8), 1273-1287.
15) Ebrahimian, Kamel; Abbasi, Ibrahim; AlamTabriz, Akbar; Mohammadzadeh, Amir (2021). Forecasting the daily trend of stock prices using text mining of sentiments of social network users
264 / Comparative Analysis on Effect of Accounting Data and Macroeconomic Variables …
Vol.9 / No.35 / Autumn 2024
and data mining of technical indicators, Investment Knowledge, Volume 10, Number 40, pp. 451-469
16) Ghysels, E., P. Santa-Clara, and R. Valkanov; (2004) .The MIDAS Touch: Mixed frequency Data Sampling Regressions, manuscript, University of NorthCarolina and UCLA. 17) Granger, C. W. J., &Machina, M. (2005). Forecasting and Decision Theory, forthcoming in the Handbook of Economic Forecasting, edited by G. Elliott, CWJ Granger and A. Timmermann. 18) Heydarzadeh Hanzaei, Alirezal; Farahani, Mohammad (1969). Investigating effect of oil price and exchange rate uncertainty on stock returns using noise-generating linear transformations and the vector autoregression model. Financial knowledge of securities analysis, volume 12, number 43, pp: 142-131. 19) Hong, Y., & Chung, J. (2003). Are the directions of stock price changes predictable? Statistical theory and evidence. Manuscript, Cornell University. 20) Kim, S. T., & Rescigno, L. (2017). Monetary policy shocks and distressed firms’ stock returns: Evidence from the publicly traded US firms. Economics letters, 160, 91-94. 21) Klein, L.R. and E. Sojo; (1989), Combinations of High and Low Frequency Data in Macroeconomic Models, Economics in Theory & Practice, :An Eclectic Approach. Kluwer Academic Publishers.pp 316 .
22) Leung, M. T., Daouk, H., & Chen, A. S. (2000). Forecasting stock indices: a comparison of classification and level estimation models. International Journal of forecasting, 16(2), 173-190. 23) MirarabBaygi, Seyed Alireza; Makari, Hashem; Nazarizadeh, Mohsen (2019). Investigating the theory of popularity in Iran's financial market and its relationship with the volatility of stock returns and stock returns in Tehran Stock Exchange, Financial Knowledge of Securities Analysis, Volume 13, Number 47, pp. 121-135. 24) Pan, L., &Politis, D. N. (2016). Bootstrap prediction intervals for linear, nonlinear and nonparametric autoregressions. Journal of Statistical Planning and Inference, 177, 1-27.
25) Rahnami Roodpashti, Fereydon; Salehi, AllahKaram (2014). Schools and theories of
finance and accounting, Central Tehran Azad University Publications 26) Rapach, D., & Zhou, G. (2013). Forecasting stock returns. In Handbook of economic forecasting (Vol. 2, pp. 328-383).Elsevier. 27) Rydberg, T. H., & Shephard, N. (2003). Dynamics of trade-by-trade price movements: decomposition and models. Journal of Financial Econometrics, 1(1), 2-25. 28) Tabatabainasab, Zohreh; Shah Moradi, Nasim (2021). Investigating effect of economic uncertainty on the dynamic relationship between profit quality and return in firms listed on the Tehran Stock Exchange with the approach of currency market pressure, Financial Knowledge of Securities Analysis, Volume 14, Number 49, pp. 131-148. 29) Westerlund, J., & Narayan, P. K. (2012). Does the choice of estimator matter when forecasting returns?. Journal of Banking & Finance, 36(9), 2632-2640. 30) Welch, I., &Goyal, A. (2008). A comprehensive look at the empirical performance of equity premium prediction. The Review of Financial Studies, 21(4), 1455-1508. 31) YousefiTarzjan, Mustafa; Safi Samaghabadi, AzamDokht; Memariani, Azizollah (2021). Stock price forecasting in the stock exchange using a combined model based on recurrent neural network and adaptive neural inference system and fuzzy expert system, Financial Engineering and Securities Management, volume 12, number 46, pp: 557-540. 32) Zainali, Gholamreza; Yazdanian, Narges (2021). Prediction of stock returns based on kernel distribution and disturbance of normal distributions, Financial engineering and securities management, volume 12, number 47, pp. 587-606. 33) Zhang, Y. J., & Li, Z. C. (2021). Forecasting the stock returns of Chinese oil companies: Can investor attention help?. International Review of Economics & Finance, 76, 531-555
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